System and method of detecting rnas altered by cancer in peripheral blood

ABSTRACT

Analyzing peripheral blood RNA populations presents an effective, accurate, minimally invasive method of determining a patient&#39;s cancer status. Using circulating free RNA of the genes disclosed herein, systems and methods are disclosed which can accurately identify cancer signatures in the patient blood samples.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Patent Application61/584,097 filed on Jan. 6, 2012 and entitled SYSTEM AND METHOD OFDETECTING RNAS ALTERED BY CANCER IN PERIPHERAL BLOOD, the entirety ofwhich is hereby incorporated by reference herein.

SEQUENCE LISTING

This application is being filed along with a sequence listing inElectronic format. The Sequence Listing is provided as a file entitledVIOMC_(—)003A_SEQUENCE_LISTING.TXT, created Jan. 3, 2013, which isapproximately 2 kb in size. The information in the electronic format ofthe sequence listing is incorporated herein by reference in its entiretyin its entirety.

FIELD OF THE INVENTION

Systems and methods for detecting cancer by assaying extracts frompatient blood are provided. In particular, methods for detectingcirculating free RNA (cfRNA) levels and relationships that are highlyspecific to patients with certain cancers are provided.

BACKGROUND

Cancer is a major health risk in the United States and internationally.Treatments exist, but are often not administered to patients until thedisease has progressed to a point at which treatment efficacy iscompromised.

A major challenge in cancer treatment is to identify patients early inthe course of their disease. This is difficult under current methodsbecause early cancerous or precancerous cell populations may beasymptomatic and may be located in regions which are difficult to accessby biopsy. Thus a robust, minimally invasive assay that may be used toidentify all stages of the disease, including early stages which may beasymptomatic, would be of substantial benefit for the treatment ofcancer.

SUMMARY OF THE INVENTION

The systems, devices, kits, and methods disclosed herein each haveseveral aspects, no single one of which is solely responsible for theirdesirable attributes. Without limiting the scope of the claims, someprominent features will now be discussed briefly. Numerous otherembodiments are also contemplated, including embodiments that havefewer, additional, and/or different components, steps, features,objects, benefits, and advantages. The components, aspects, and stepsmay also be arranged and ordered differently. After considering thisdiscussion, and particularly after reading the section entitled“Detailed Description,” one will understand how the features of thedevices and methods disclosed herein provide advantages over other knowndevices and methods.

One embodiment is a method for detection of one or more RNA molecules insamples taken from a patient. In this embodiment, blood or bloodcomponent such as plasma is isolated from a patient suspected of havinglung cancer or non-small cell lung cancer (NSCLC). The plasma isanalyzed to measure the level of circulating free RNA (cfRNA) from oneor more genes. In some embodiments the RNA to be measured is messengerribonucleic acids (mRNA), such as mRNA from within the population ofcfRNA in a patient's plasma. In some embodiments the level ofcirculating free actin beta (ACTB) RNA is measured. In some embodimentsthe level of circulating free HNRNPA1 RNA is measured. In someembodiments, the level of circulating free formylpeptide receptor gene(FPR1) RNA is measured. In some embodiments, the level of cfRNA fromFPR1, as compared with the level of cfRNA from ACTB and HNRNPA1 iscompared, as discussed below, to determine if a patient is at risk forhaving lung cancer or NSCLC. In some embodiments the NSCLC assayed isStage I NSCLC.

In some embodiments, at least one subset of one or more RNAs (subset #2)is known to be present in plasma of cancer-free individuals inrelatively consistent quantities, and is known to be present at a leveldifferent from this generally consistent level in individuals withcancer such as breast, colon or lung cancer. For example, levels may beconsistently lower in, for example patients having non-small cell lungcancer (NSCLC), such as stage I NSCLC. In some embodiments levels may beconsistently higher in patients having cancer, for example patientshaving non-small cell lung cancer (NSCLC), such as stage I NSCLC. Insome embodiments the lung cancer of said individuals does not showmetastasis to the lymph nodes. In some embodiments, the RNA(s) selectedfor subset #1 may be present in lower levels due to nuclease activity,and in some embodiments the RNA or region of the RNA assayed for may behighly sensitive to nucleases due to the presence of nuclease cleavagesites or the presence of secondary structures (i.e. double vs. singlestranded) that are preferentially cleaved by RNases. In some embodimentsthe RNA selected for subset #1 may be represented in higher levels incertain cancer patients, such as lung cancer patients. In someembodiments, the change in levels of RNA accumulation in subset #1 maybe due to effects of molecules secreted by cancers or immune cellswithin close proximity to tumors on other non-malignant tissues.

In some embodiment, RNAs in subset #1 are released into the blood atincreased levels in cancer patients due to one or more of thefollowing: 1) preferential release from cells into the blood, 2)increased abundance in tumor cells, 3) increased abundance in cells nearthe tumor (i.e. reactive cells or stroma), 4) increased abundance fromcells not near the tumor, mediated by secreted signals.

Another subset of one or more RNAs (subset #2) may be known to be stablyexpressed in all individuals regardless of cancer status. In someembodiments, the RNAs in subset #2 are less sensitive to ribonucleases.

In some embodiments, relative abundance of markers of subset #1 andsubset #2 may be indicative of the presence of cancerous cells, tumors,or cells with a heightened potential to become cancerous, and in otherembodiments, the accumulation levels of markers in subset #1 alone maybe indicative of cancerous cells, tumors, or cells with a heightenedpotential to become cancerous. In some embodiments the RNA levels of asubset #2 member or members may vary inversely with the levels of asubset #1 member or member, such that the ratio of the levels isindicative of cancer status.

In some embodiments, digital PCR or real-time PCR is used as a detectionmethod to determine the presence or accumulation levels of RNA markers.In some embodiments, DNA sequencing may be used as a detection method todetermine the quantity of RNA markers. In other embodiments, detectionmay occur by molecular barcoding technologies such as NanoString ornCounter.

In some embodiments, the results of RNA and/or DNA copy number areanalyzed to determine an assay outcome (i.e., positive or negativeresult) based at least in part on statistical distances between results.In some aspects, patients may be classified into different risk groupsbased at least in part on the analysis of the relative abundance ofmarkers as disclosed herein. The cumulative distribution function of thenormal, binomial and/or Poisson distribution or similar functions may beused to determine relative abundance of RNAs. In some embodiments, thetype of cancer present in a patient may be predicted at least in part onresults of RNA expression.

BRIEF DESCRIPTION OF FIGURE DRAWINGS

FIGS. 1A, 1B, and 1C depicts box plots of accumulation levels for themarkers FPR1, ACTB and HNRNPA1, respectively, from plasma taken fromnormal individuals and individuals known to have one or more tumors. They-axis indicates the transcript accumulation level per mL of plasmaassayed, normalized against accumulation levels measured in UniversalHuman Reference RNA, represented natural logarithmically. According tothe standard convention for boxplots, the central horizontal line ineach column represents the median, the box represents the 25%-75%quartiles and the error bars indicate the extreme observations(excluding outliers). All units are ratios of transcript accumulationlevels per mL of plasma assayed relative to accumulation levels ofsimilar transcripts obtained from 1 ng of Agilent's Universal Human RNA.

FIG. 2A depicts two-dimensional scatter-plots of ratios ACTB and HNRNPA1values normalized to FPR1 values, wherein sample values are normalizedto values determined from RNA obtained from a cell line control. Dashedline A separates the majority of values obtained from Normal patients.Dashed line B separates the majority of values obtained from NSCLCpatients. The values between dashed lines A and B represent the minimaldegree of overlap between the highest Normal values and the lowest NSCLCvalues.

FIG. 2B depicts two-dimensional scatter-plots of ratios ACTB and HNRNPA1values normalized to FPR1 values, wherein sample values are normalizedto values determined from RNA obtained from a synthetic standard. Thedashed diagonal line passing through the points (0.1, 10), (1, 1) and(10, 0.1) separates a population of normal samples (white-filledcircles) from a population of predominantly NSCLC samples (black-filledcircles).

DETAILED DESCRIPTION

One embodiment relates systems and methods for determining whether apatient at risk for cancer may have the disease by analyzing circulatingnucleic acids in the blood. Determination of patients that may havecancer may be done on blood-derived specimens to assay RNA accumulationlevels, and such analysis may be conducted by expression microarray,sequencing, nCounter, or real-time PCR. In some embodiments, expressionlevels of first subset of control nucleic acids are compared toexpression levels of a second subset of nucleic acids that are known tobe increased in patients having cancer. The first subset of controlnucleic acids may be found by analyzing plasma from many disease-freepatients and selecting genes that are expressed at stable levels withinthose patients. Subsets may also be found by analyzing solid tissuespecimens taken from multiple tissue types (i.e. colon, lung, kidney,liver, etc.), and selecting genes that are expressed as circulating freenucleic acids at stable levels in a patient's blood.

In some embodiments, Subset #1 can be selected by analyzing genes whosetranscript accumulation levels increase in plasma or in solid tumorspecimens.

In some embodiments, Subset #1 includes genes whose circulating freenucleic acid levels decrease in plasma or in solid tumor specimens takenfrom individuals suffering from cancer.

In some embodiments, subset #1 comprises genes whose transcriptaccumulation levels are unchanged in normal individuals as compared tocancer patients. In these embodiments subset #2 is selected incombination with one or more genes of subset #1 whose accumulationlevels increase in plasma or in solid tumors specimens.

In some embodiment, aspects of the invention relate to the discoverythat circulating free RNA (cfRNA) levels of formylpeptide receptor gene(FPR1) RNA change in patients suffering from cancer. For example, cfRNAlevels of FPR1 were found to increase in patients having lung cancer, asdescribed below. Moreover, cfRNA levels of FPR1 were shown to increasein comparison to cfRNA levels of other genes, such as ACTB and HNRNPA1or other transcripts listed in subset #2.

As shown in FIG. 1A and described with reference to Example 1, FIG. 1Adepicts transcript accumulation levels for the gene FPR1 in samplesmeasured from plasma taken from patients classified as having a cancerstatus as either normal (i.e., putatively cancer free) and tumor cells(i.e., having known tumor cells). The y-axis logarithmic values indicatethat the FPR1 transcript accumulates on average at about a 100-foldgreater level in tumor cell patients as compared to normal patients.

FIG. 1B and FIG. 1C depict transcript accumulation levels for the genesACTB and HNRNPA1, respectively, in samples measured from plasma takenfrom patients classified as having a cancer status as either normal(i.e., putatively cancer free) and tumor cells (i.e., having known tumorcells). The y-axis logarithmic values indicate that the ACTB and HNRNPA1transcripts accumulate on average at levels which are comparable innormal and in tumor cell patients.

In some embodiments, once subset #1 is known, subset #2 can be selectedby analyzing a large number of candidates from multiple specimens andselecting those for which the difference between subset #2 and subset #1is largest in plasma from cancer patients. In some embodiments, subset#2 can be selected by surveying transcript accumulation levels of manygenes and finding which ones have the lowest variability. In someembodiments genes are selected not based on their individualaccumulation levels but on the lack of change in their relativeaccumulation levels in cancer.

FIGS. 1A-C indicate that FPR1 and ACTB, FPR1 and HNRNPA1, or FPR1 andboth ACTB and HNRNPA1 are suitable combinations of subset#1 and subset#2 genes for the methods disclosed herein, although embodiments of theinvention are not limited to only these genes.

Once subset #1 (and subset #2 in some embodiments) are known within agiven cancer type, the expression profile can be measured in plasmataken from cancer patients and patients for which a cancer is to beassayed. Because plasma can be collected and prepared within manyprimary care physician offices without posing any more risk than astandard blood draw, relative cfRNA accumulation levels between subsets#1 and subset #2 in some embodiments may be a valuable cancer biomarker.Additionally, if subsets #1 and subset #2 in some embodiments may beassayed reliably, they may have a number of advantages over currentcancer assays. For example, in some embodiments this method may detectcancer at an early stage of development, cancer that poses few symptoms,cancer that is difficult to distinguish from benign conditions or cancerthat may be developing in an area of the body that may not be accessibleto traditional biopsy assays.

Increased RNase activity is often present in tumors. This RNase activitymay inhibit tumor growth, and may be part of the immune system'sresponse to cancer. Cytotoxic T cells may lead to apoptosis of cancercells via IFN-γ, and this apoptosis may result in activation of RNases,such as RNase L. Death of cells via necrosis, which may be caused byhypoxia due to tumor growth, may also contribute to the release ofRNases. It is known that plasma of lung cancer patients has increasedRNase activity (Marabella et al., (1976) “Serum ribonuclease in patientswith lung carcinoma,” Journal of Surgical Oncology, 8(6):501-505; Reddiet al. (1976) “Elevated serum ribonuclease in patients with pancreaticcancer,” Proc. Nat'l. Acad. Sci. USA 73(7):2308-2310). It is also knownthat lung cells contain RNases similar to those found in plasma (Neuweltet al., (1978) “Possible Sites of Origin of Human Plasma Ribonucleasesas Evidenced by Isolation and Partial Characterization of Ribonucleasesfrom Several Human Tissues,” Cancer Research 38:88-93).

When higher levels of RNase are present in plasma, any free RNA issusceptible to more rapid degradation. Thus, there may be less RNAdetectable in plasma RNA preparations. While all RNA may be present atdecreased levels, it is only possible to detect this difference with anylevel of accuracy when the normal variability of a gene is low. Forexample, if the normal range of a gene's expression is between 10 and100 units, it may be difficult to accurately detect a decrease of 1unit. However, if a gene's expression is normally between 10 and 11units, a decrease of 1 unit is readily detectable (i.e. any number under10 units would indicate a decrease).

FPR1 plays multiple roles in the lungs and cancer. FPR1 is expressed inlung fibroblasts (VanCompernolle et al. (2003) J Immunol. 171(4):2050-6)and is necessary for wound repair in the lungs (Shao (2011) Am J RespirCell Mol Biol 44:264-269). It is known that fibroblasts are important inboth attracting immune cells that fight the tumor (Gemperle (2012)PLOSOne 7(11):1-7, e50195) and creation of stroma which protects thetumor (Wang (2009) Clin Cancer Res 15(21) 6630-6638). FPR1 may alsoexacerbate the activity of other oncogenes in tumors (Huang (2007)Cancer Res 67(12):5906-5913). There is no evidence that it isoverexpressed in lung cancers, but FPR1 is known to be regulated by RNAstabilization (Mandal (2007) J Immunol 178:2542-2548, Mandal (2005) JImmunol 175:6085-6091). Given these roles, it is possible that FPR1 RNAis secreted deliberately by either tumor cells to enhance tumor growth(i.e. by activating wound-repair systems for growth or growingprotective stroma) or immune cells to enhance the immune response (i.e.attracting additional immune cells).

In some embodiments the method can begin by extracting cfRNA from apatient's sample and assaying the cfRNA extracted. See, e.g.,O'Driscoll, L. et al. (2008) “Feasibility and relevance of globalexpression profiling of gene transcripts in serum from breast cancerpatients using whole genome microarrays and quantitative RT-PCR.” CancerGenomics Proteomics 5:94-104, which is hereby incorporated by referencein its entirety. In some embodiments, a consistent, repeatable method isused to isolate cfRNA from plasma or other source of RNA to ensure thereliability of the data. To obtain cfRNA from blood, one may use theprotocol listed below although other methods are also contemplated.

cfRNA molecules may be purified from plasma or other samples using, forexample, Qiagen's QIAamp circulating nucleic acid kit. The protocol inthis kit is described in the document “QIAamp Circulating Nucleic AcidHandbook”, Second Edition, January 2011, which is hereby incorporated byreference in its entirety. This protocol provides an embodiment of amethod to purify circulating total nucleic acid from 1 mL of plasma. Inbrief, lysis reagents and proteases are added along with inert carrierRNA. The total nucleic acid (DNA and RNA) is bound to a column, and thecolumn is washed multiple times then eluted off the column.

For example the protocol may be performed by executing the steps asfollows. Pipet 100 μl, 200 μl, or 300 μl QIAGEN Proteinase K into a 50ml centrifuge tube. Add 1 ml, 2 ml, or 3 ml of serum or plasma to the 50ml tube. Add 0.8 ml, 1.6 ml, or 2.4 ml Buffer ACL (containing 1.0 μgcarrier RNA). Close the cap and mix by pulse-vortexing for 30 s, makingsure that a visible vortex forms in the tube. In order to ensureefficient lysis, mix the sample and Buffer ACL thoroughly to yield ahomogeneous solution. The procedure should not be interrupted at thistime.

To start the lysis incubation, incubate at 60° C. for 30 min. Place thetube back on the lab bench and add 1.8 ml, 3.6 ml, or 5.4 ml Buffer ACBto the lysate in the tube. Close the cap and mix thoroughly bypulse-vortexing for 15-30 seconds. Incubate the lysate-Buffer ACBmixture in the tube for 5 min on ice. Insert the QIAamp Mini column intothe VacConnector on the QIAvac 24 Plus. Insert a 20 ml tube extenderinto the open QIAamp Mini column. Make sure that the tube extender isfirmly inserted into the QIAamp Mini column in order to avoid leakage ofsample.

Keep the collection tube for the dry spin, below. Carefully apply thelysate-Buffer ACB mixture into the tube extender of the QIAamp Minicolumn. Switch on the vacuum pump. When all lysates have been drawnthrough the columns completely, switch off the vacuum pump and releasethe pressure to 0 mbar. Carefully remove and discard the tube extender.Please note that large sample lysate volumes (about 11 ml when startingwith 3 ml sample) may need up to 10 minutes to pass through the QIAampMini membrane by vacuum force. For fast and convenient release of thevacuum pressure, the Vacuum Regulator should be used (part of the QIAvacConnecting System). To avoid cross-contamination, be careful not to movethe tube extenders over neighboring QIAamp Mini Columns.

Apply 600 μl Buffer ACW1 to the QIAamp Mini column. Leave the lid of thecolumn open, and switch on the vacuum pump. After all of Buffer ACW1 hasbeen drawn through the QIAamp Mini column, switch off the vacuum pumpand release the pressure to 0 mbar. Apply 750 μl Buffer ACW2 to theQIAamp Mini column. Leave the lid of the column open, and switch on thevacuum pump. After all of Buffer ACW2 has been drawn through the QIAampMini column, switch off the vacuum pump and release the pressure to 0mbar. Apply 750 μl of ethanol (96-100%) to the QIAamp Mini column. Leavethe lid of the column open, and switch on the vacuum pump. After all ofethanol has been drawn through the spin column, switch off the vacuumpump and release the pressure to 0 mbar. Close the lid of the QIAampMini column. Remove it from the vacuum manifold, and discard theVacConnector. Place the QIAamp Mini column in a clean 2 ml collectiontube, and centrifuge at full speed (20,000×g; 14,000 rpm) for 3 min.

Place the QIAamp Mini Column into a new 2 ml collection tube. Open thelid, and incubate the assembly at 56° C. for 10 min to dry the membranecompletely. Place the QIAamp Mini column in a clean 1.5 ml elution tube(provided) and discard the 2 ml collection tube from step 14. Carefullyapply 20-150 μl of Buffer AVE to the center of the QIAamp Mini membrane.Close the lid and incubate at room temperature for 3 min. Ensure thatthe elution buffer AVE is equilibrated to room temperature (15-25° C.).If elution is done in small volumes (<50 μl) the elution buffer has tobe dispensed onto the center of the membrane for complete elution ofbound DNA. Elution volume is flexible and can be adapted according tothe requirements of downstream applications. The recovered eluate volumewill be up to 5 μl less than the elution volume applied to the QIAampMini column. Centrifuge in a microcentrifuge at full speed (20,000×g;14,000 rpm) for 1 min to elute the nucleic acids. The above exampleQIAamp Circulating Nucleic Acid Handbook 1/2011 is representative onknowledge of one of skill in the art and it illustrative rather thanlimiting. Alternate embodiments, including variants on the methods aboveor distinct approaches to cfRNA purification, are contemplated herein,and the methods and compositions disclosed herein are not limited to anyparticular cfRNA purification method.

Samples produced by this method may be highly pure and free of PCRinhibitors, and may be suitable for qPCR as used in some embodiments toassay cfRNA relative expression as an assay of, for example, varioustypes of cancer.

In some embodiments the methods include performing PCR or qPCR in orderto generate an amplicon. Numerous different PCR and qPCR protocols areknown in the art and exemplified herein below and can be directlyapplied or adapted for use using the presently described compositionsfor the detection and/or identification of

Some embodiments provide methods including Quantitative PCR (qPCR) (alsoreferred as real-time PCR). qPCR can provide quantitative measurements,and also provide the benefits of reduced time and contamination. As usedherein, “quantitative PCR” (“qPCR” or more specifically “real timeqPCR”) refers to the direct monitoring of the progress of a PCRamplification as it is occurring without the need for repeated samplingof the reaction products. In qPCR, the reaction products may bemonitored via a signaling mechanism (e.g., fluorescence) as they aregenerated and are tracked after the signal rises above a backgroundlevel but before the reaction reaches a plateau. The number of cyclesrequired to achieve a detectable or “threshold” level of fluorescence(herein referred to as cycle threshold or “CT”) varies directly with theconcentration of amplifiable targets at the beginning of the PCRprocess, enabling a measure of signal intensity to provide a measure ofthe amount of target nucleic acid in a sample in real time.

Methods for setting up PCR and qPCR are well known to those skilled inthe art. The reaction mixture minimally comprises template nucleic acid(e.g., as present in test samples, except in the case of a negativecontrol as described below) and oligonucleotide primers and/or probes incombination with suitable buffers, salts, and the like, and anappropriate concentration of a nucleic acid polymerase. As used herein,“nucleic acid polymerase” refers to an enzyme that catalyzes thepolymerization of nucleoside triphosphates. Generally, the enzyme willinitiate synthesis at the 3′-end of the primer annealed to the targetsequence, and will proceed in the 5′-3′ direction along the templateuntil synthesis terminates. An appropriate concentration includes onethat catalyzes this reaction in the presently described methods. KnownDNA polymerases useful in the methods disclosed herein include, forexample, E. coli DNA polymerase I, T7 DNA polymerase, Thermusthermophilus (Tth) DNA polymerase, Bacillus stearothermophilus DNApolymerase, Thermococcus litoralis DNA polymerase, Thermus aquaticus(Taq) DNA polymerase and Pyrococcus furiosus (Pfu) DNA polymerase,FASTSTART™ Taq DNA polymerase, APTATAQ™ DNA polymerase (Roche), KLENTAQ1™ DNA polymerase (AB peptides Inc.), HOTGOLDSTAR™ DNA polymerase(Eurogentec), KAPATAQ™ HotStart DNA polymerase, KAPA2G™ Fast HotStartDNA polymerase (Kapa Biosystemss), PHUSION™ Hot Start DNA Polymerase(Finnzymes), or the like.

In addition to the above components, the reaction mixture of the presentmethods includes primers, probes, and deoxyribonucleoside triphosphates(dNTPs).

Usually the reaction mixture will further comprise four different typesof dNTPs corresponding to the four naturally occurring nucleoside bases,i.e., dATP, dTTP, dCTP, and dGTP. In some embodiments, each dNTP willtypically be present in an amount ranging from about 10 to 5000 μM,usually from about 20 to 1000 μM, about 100 to 800 μM, or about 300 to600 μM.

The reaction mixture can further include an aqueous buffer medium thatincludes a source of monovalent ions, a source of divalent cations, anda buffering agent. Any convenient source of monovalent ions, such aspotassium chloride, potassium acetate, ammonium acetate, potassiumglutamate, ammonium chloride, ammonium sulfate, and the like may beemployed. The divalent cation may be magnesium, manganese, zinc, and thelike, where the cation will typically be magnesium. Any convenientsource of magnesium cation may be employed, including magnesiumchloride, magnesium acetate, and the like. The amount of magnesiumpresent in the buffer may range from 0.5 to 10 mM, and can range fromabout 1 to about 6 mM, or about 3 to about 5 mM. Representativebuffering agents or salts that may be present in the buffer includeTris, Tricine, HEPES, MOPS, and the like, where the amount of bufferingagent will typically range from about 5 to 150 mM, usually from about 10to 100 mM, and more usually from about 20 to 50 mM, where in certainpreferred embodiments the buffering agent will be present in an amountsufficient to provide a pH ranging from about 6.0 to 9.5, for example,about pH 6.0, 6.5, 7.0, 7.5, 8.0, 8.5, 9.0, or 9.5. Other agents thatmay be present in the buffer medium include chelating agents, such asEDTA, EGTA, and the like. In some embodiments, the reaction mixture caninclude BSA, or the like. In addition, in some embodiments, thereactions can include a cryoprotectant, such as trehalose, particularlywhen the reagents are provided as a master mix, which can be stored overtime.

In preparing a reaction mixture, the various constituent components maybe combined in any convenient order. For example, the buffer may becombined with primer, polymerase, and then template nucleic acid, or allof the various constituent components may be combined at the same timeto produce the reaction mixture.

Alternatively, commercially available premixed reagents can be utilizedin the methods disclosed herein, according to the manufacturer'sinstructions, or modified to improve reaction conditions (e.g.,modification of buffer concentration, cation concentration, or dNTPconcentration, as necessary), including, for example, Quantifast PCRmixes (Qiagen), TAQMAN® Universal PCR Master Mix (Applied Biosystems),OMNIMIX® or SMARTMIX® (Cepheid), IQ&#8482; Supermix (Bio-RadLaboratories), LIGHTCYCLER® FastStart (Roche Applied Science,Indianapolis, Ind.), or BRILLIANT® QPCR Master Mix (Stratagene, LaJolla, Calif.).

The reaction mixture can be subjected to primer extension reactionconditions (“conditions sufficient to provide polymerase-based nucleicacid amplification products”), i.e., conditions that permit forpolymerase-mediated primer extension by addition of nucleotides to theend of the primer molecule using the template strand as a template. Inmany embodiments, the primer extension reaction conditions areamplification conditions, which conditions include a plurality ofreaction cycles, where each reaction cycle comprises: (1) a denaturationstep, (2) an annealing step, and (3) a polymerization step. As discussedbelow, in some embodiments, the amplification protocol does not includea specific time dedicated to annealing, and instead comprises onlyspecific times dedicated to denaturation and extension. The number ofreaction cycles will vary depending on the application being performed,but will usually be at least 15, more usually at least 20, and may be ashigh as 60 or higher, where the number of different cycles willtypically range from about 20 to 40. For methods where more than about25, usually more than about 30 cycles are performed, it may beconvenient or desirable to introduce additional polymerase into thereaction mixture such that conditions suitable for enzymatic primerextension are maintained.

The denaturation step comprises heating the reaction mixture to anelevated temperature and maintaining the mixture at the elevatedtemperature for a period of time sufficient for any double-stranded orhybridized nucleic acid present in the reaction mixture to dissociate.For denaturation, the temperature of the reaction mixture will usuallybe raised to, and maintained at, a temperature ranging from about 85 to100° C., usually from about 90 to 98° C., and more usually from about 93to 96° C., for a period of time ranging from about 3 to 120 sec, usuallyfrom about 3 sec.

Following denaturation, the reaction mixture can be subjected toconditions sufficient for primer annealing to template nucleic acidpresent in the mixture (if present), and for polymerization ofnucleotides to the primer ends in a manner such that the primer isextended in a 5′ to 3′ direction using the nucleic acid to which it ishybridized as a template, i.e., conditions sufficient for enzymaticproduction of primer extension product. In some embodiments, theannealing and extension processes occur in the same step. Thetemperature to which the reaction mixture is lowered to achieve theseconditions will usually be chosen to provide optimal efficiency andspecificity, and will generally range from about 50 to 85° C., usuallyfrom about 55 to 70° C., and more usually from about 60 to 68° C. Insome embodiments, the annealing conditions can be maintained for aperiod of time ranging from about 15 sec to 30 min, usually from about20 sec to 5 min, or about 30 sec to 1 minute, or about 30 seconds.

This step can optionally comprise one of each of an annealing step andan extension step with variation and optimization of the temperature andlength of time for each step. In a two-step annealing and extension, theannealing step is allowed to proceed as above. Following annealing ofprimer to template nucleic acid, the reaction mixture will be furthersubjected to conditions sufficient to provide for polymerization ofnucleotides to the primer ends as above. To achieve polymerizationconditions, the temperature of the reaction mixture will typically beraised to or maintained at a temperature ranging from about 65 to 75°C., usually from about 67 to 73° C. and maintained for a period of timeranging from about 15 sec to 20 min, usually from about 30 sec to 5 min.In some embodiments, the methods disclosed herein do not include aseparate annealing and extension step. Rather, the methods includedenaturation and extension steps, without any step dedicatedspecifically to annealing.

The above cycles of denaturation, annealing, and extension may beperformed using an automated device, typically known as a thermalcycler. Thermal cyclers that may be employed are described elsewhereherein as well as in U.S. Pat. Nos. 5,612,473; 5,602,756; 5,538,871; and5,475,610; the disclosures of which are herein incorporated byreference.

The methods described herein can also be used in non-PCR basedapplications to detect a target nucleic acid sequence, where such targetmay be immobilized on a solid support. Methods of immobilizing a nucleicacid sequence on a solid support are known in the art and are describedin Ausubel et al, eds. (1995) Current Protocols in Molecular Biology(Greene Publishing and Wiley-Interscience, NY), and in protocolsprovided by the manufacturers, e.g., for membranes: Pall Corporation,Schleicher &amp; Schuell; for magnetic beads: Dynal; for culture plates:Costar, Nalgenunc; for bead array platforms: Luminex and BectonDickinson; and, for other supports useful according to the embodimentsprovided herein, CPG, Inc.

Variations on the exact amounts of the various reagents and on theconditions for the PCR or other suitable amplification procedure (e.g.,buffer conditions, cycling times, etc.) that lead to similaramplification or detection/quantification results are known to those ofskill in the art and are considered to be equivalents. In oneembodiment, the subject qPCR detection has a sensitivity of detectingfewer than 50 copies (preferably fewer than 25 copies, more preferablyfewer than 15 copies, still more preferably fewer than 10 copies, e.g.5, 4, 3, 2, or 1 copy) of target nucleic acid in a sample.

In some embodiments the method may involve PCR amplification of cfRNAtemplate RNA. A DNase treatment may be conducted to remove DNAcontamination from RNA samples. cfRNA may be converted to cDNA with areverse transcriptase and this step may use one or more of the sameprimers used within a PCR reaction. Target cDNAs may be amplified by,for example, a consistent, repeatable method to amplify cDNA from plasmaor other cDNA. In some embodiments, one or more targets in cDNA may beamplified and quantified via Taqman chemistry. This protocol may not bethe only suitable protocol to detect cfRNA quantity. However, it may beimportant to use a consistent protocol for cDNA synthesis andamplification, as variations in protocol may have a large effect on theeventual results.

In some embodiments the method may involve an assay for non-small celllung cancers (NSCLC). In some embodiments, an assay may involve one ormore of the following genes to comprise subset #2: PLGLB2, GABARAP,HNRNPA1, NACA, EIF1, UBB, UBC, CD81, TMBIM6, MYL12B, ACTB, HSP90B1,CLDN18, RAMP2, MFAP4, FABP4, MARCO, RGL1, ZBTB16, C10orf116, GRK5, AGER,SCGB1A1, HBB, TCF21, GMFG, HYAL1, TEK, GNG11, ADH1A, TGFBR3, INPP1,ADH1B; and one or more of the following genes to comprise subset #1:CTSS, FPR1, FPR2, FPRL1, FPRL2, CXCR2, NCF2.

A proprietary R1b assay may be used. In this embodiment, the assay maybe a 3-plex qPCR assay that detects relative abundance of ACTB, HNRNPA1and FPR1. In some embodiments ACTB and HNRNPA1 may fulfill the criteriafor subset #2, and FPR1 may fulfill the criteria for subset #1.

In some embodiments, the subset #2 may consist of ACTB and subset #1 mayconsist of FPR1. In some embodiments the subset #2 may consist ofHNRNPA1. In some embodiments the subset #2 may consist of ACTB andHNRNPA1. In some embodiments the subset #2 may comprise at least one ofACTB and HNRNPA1. In some embodiments subset #1 is FPR1 and Subset #2 isACTB, or HNRNP1, or both ACTB and HNRNP1. In some embodiments, Qiagenassay #QF00119602 may be used for the qPCR, using the primers/probesprovided accorded to the manufacturer's protocol. Agilent's UniversalRNA may be used as a standard in qPCR. In another embodiment, the R1bassay consisting of the following primer/probes may be as follows inTable 1.

TABLE 1 Amplification Primers Gene Forward Primer Probe Reverse PrimerFPR1 TGACGGTGAGAGG [FAM] GGTGGCAATAAGCCCA CATCA CGGTTCATCATTGGCTTCAGTAACTG (SEQ ID NO: 3) (SEQ ID NO: 1) CGC [BHQ1](SEQ ID NO: 2) ACTBAGGCCAACCGCGA [CAL Fluor Gold 540] TGCCATCCTAAAAGCC GAAGATGACCCAGATCATGTTTGAG ACCCCA (SEQ ID NO: 6) (SEQ ID NO: 4) ACCTTCA [BHQ1](SEQ ID NO: 5) HNRN GGGCTTTGCCTTTG [Quasar 705] TGTGGCCATTCACAGT PA1TAACCTT TGACGACCATGACTCCGTGG ATGGTA (SEQ ID NO: 9) (SEQ ID NO: 7)ATA [BHQ3] (SEQ ID NO: 8)

An RNA standard may be used to standardize result across multiple runs.This standard may be run at different dilutions. In some embodiments asynthetic standard may be used. For example, the normal ranges andcut-offs for one or more markers may be examined, and syntheticstandards may be obtained and used directly, or diluted or combined suchthat they are at levels similar to predicted levels, such as predictedlevels of the markers. In some embodiments the synthetic standards arepresent at levels that are at or within an order of magnitude of (i.e.,10-fold higher or 10-fold lower than) predicted levels in a patientsample. In some embodiments the synthetic standards are present at orwithin a difference of 5× (either 5-fold higher or five-fold lower) thanlevels predicted for a patient sample. In some embodiments the syntheticstandards are present at or within a difference of 2× (either 2-foldhigher or 2-fold lower) than levels predicted for a patient sample.

Many methods may be used to determine the appropriate level of eachsynthetic RNA in the synthetic standard. In one embodiment, one may runsome number of samples representative of those and record the results(i.e. Ct value or fitted value to a standard). Each synthetic RNA maythen be run on the same assay and the results may be measured on thesame scale as the samples (i.e. Ct score or fitted value to a standard).Upon examination, one can determine which standards must be used. Forexample, 50 samples may be run and Ct scores ranging from 33-38 areobtained for a given gene. Standards of 10⁷, 10⁶, 10⁵, 10⁴, 10³, 10²copies per μL may yield Ct scores of 24, 28, 32, 36, 40, or 44. Thus, itmay be decided to use the 10⁵ standard, with dilutions to 10⁴ and 10³conducted during assay setup. Using this strategy, only the originalstandard and two dilutions are needed to cover future samples. A similarmethod could be used to select appropriate concentrations for otherstandards in the same multiplex. Using this method, differentconcentrations may be used for each transcript to be assayed so a singlestandard can be used even if there are large discrepancies betweendifferent genes in the multiplex. By using the method disclosed herein,transcripts of widely ranging accumulation levels may be assayed with areduced number of amplification reactions on standard templates.

For example, if one expects gene A to be in the range of 100 to 10,000copies/μl and gene B to be in the range of 1,000,000 to 100,000,000copies, one may create a mixed synthetic standard of 10,000 copies geneA and 100,000,000 copies gene B, thereby only requiring three standardsin a 10-fold dilution series to cover the whole range expected for asample. Using such a synthetic standard may in some embodimentsdramatically reduce the number of standard or control samples that needto be run in a qPCR reaction plate to generate a standard curve thatcovers the expected ranges of both gene a and gene B. This method willalso minimize risk of small errors introduced by pipetting fromcompounding during serial dilutions.

Regression may be used to fit data points generated from patient samplesto the standard, such that results are expressed in standard units. Insome embodiments, the standard consists of RNA created from one or morecell lines. In some embodiments, the standard may consist of syntheticRNAs. The number of fragments of each RNA within the standard may beknown, and the standardized unit may be number of RNA molecules presentfor each target. In some embodiments, the standard may consist of thefollowing synthetic RNAs:

Target Synthetic RNA sequence FPR15′CAUGUUGACGGUGAGAGGCAUCAUCCGGUUCAUCAUUGGCUUCAGCGCACCCAUGUCCAUCGUUGCUGUCAGUUAUGGGCU UAUUGCCACCAAGAU3'(SEQ ID NO: 10) ACTB 5′CCCCAAGGCCAACCGCGAGAAGAUGACCCAGAUCAUGUUUGAGACCUUCAACACCCCAGCCAUGUACGUUGCUAUCCAGGC UGUGCUAUCCC3' (SEQ ID NO: 11)HNRNPA1 5′AAAAGGGGCUUUGCCUUUGUAACCUUUGACGACCAUGACUCCGUGGAUAAGAUUGUCAUUCAGAAAUACCAUACUGUGAAU GGCCACAACUGU3′ (SEQ ID NO: 12)

Assays may involve components of different sequence or with differentdetectable labels targeted to similar regions, components targeted todifferent regions of the same genes, or components targeting the regionsof genes other than those listed in the R1a assay above.

The results of an R1a test may be evaluated using the Decision Rules forViomics' Test for cancer such as Viomics' NSCLC Test. A plot may becreated where one axis is the ratio of FPR1 to ACTB, and the other axisis the ratio of FPR1 to HNRNPA1. An example of such a plot is indicatedin FIGS. 2A-B. The plot in FIG. 2A is the initial data using a cell linecontrol, and the plot in FIG. 2B is an independent data set that uses asynthetic standard.

When a cell line control is used, NSCLC and Normal Sample results aresignificantly different from one another. Despite the presence of someoverlap, NSCLC samples consistently show ACTB to FPR1 ratios and HNRNPA1to FPR1 ratios that are significantly greater than non-cancer sampleswhen fit to a cell line control.

When a synthetic RNA standard rather than a cell line control is used,similar results are obtained but the degree of overlap is substantiallydecreased. This decreased overlap is due to decreased variability in thestandards resulting from reduced numbers of serial dilutions (from 6 to3). Each step of the serial dilution may introduce error. In FIG. 2B, asimple line can be drawn to separate all but one of the Normal syntheticstandard result ratios from all of the NSCLC results.

The results may also be interpreted as a single ratio between a linearcombination of the type #1 markers and a linear combination of the type#2 markers. A decision rule may state that any score above a giventhreshold indicates cancer, while a score below the threshold indicatesthe lack of cancer. A synthetic standard may be designed such that thecoefficient on each marker is 1, such that the score is calculated as:Score=FRP1/(ACTB+HNRNPA1).

For example, transcript accumulation values for genes selected from thelists above may be determined from a sample and compared to levelsdetermined from a set of synthetic standards (i.e. in a serial dilutionseries) that span the range of values that are typically obtained. Foreach gene, the transcript accumulation level determined from a patientsample is compared to the transcript accumulation level determined byperforming a regression analysis on a synthetic standard template to fitthe accumulation level values for each gene. The regression and fittedvalues are obtained for each gene individually. Additional analysis(i.e. calculating ratios) may be done once fitted values are obtained.

These scores may be compared to threshold values, such that scores abovea threshold are indicative of a heightened risk of lung cancer asindicated by a patient sample.

It can be readily seen that, when this calculation is used with athreshold of ½, it is the same as using the line drawn in FIG. 2B. Thecorrect concentrations for each standard, coefficients and threshold maybe determined by collecting data on a small set of samples from bothcancer and cancer-free patients, then using a linear model to separatethem. The linear model may be generated via a statistical method such aslogistic regression or support vector machines with a linear kernelfunction, or the linear model may be generated by inspection.

Exclusionary criteria may be implemented, such that any sample thatmeets the exclusionary criteria has no result reported. Theseexclusionary criteria may include other test preformed before or afterone of the described embodiments. The exclusionary criteria may also bebased on results of the test itself. For example, in some embodimentsvery low quantities of the markers indicate a degraded sample, and anunexpectedly large ratio between two accumulation levels such as thoseof ACTB and HNRNPA1, for example, may indicate that there iscontamination. In some embodiments a sample is excluded if the ratio ofACTB to HNRNPA1 differs by more than 10, 5, 4, 3, or 2-folded comparedto the median ratio of the accumulation levels of the genes. One exampleof a plausible contamination source is that of lymphocytes in the plasmasample.

In some embodiments the method may involve a Statistical DistanceDetermination. Because cfRNA from cancer cells may be highly diluted, amethod may be required to determine significant changes in relativeabundance. For this reason, in some embodiments, the method determinesthe assay outcome (i.e., positive or negative result) based onstatistical distances between results as opposed to a fixed cutoffdetermined only through ROC curves.

Based on the specificity, the results may be divided into groups (highconfidence, low confidence, etc.). This number may also be transformedby some simple formula to create a numerical score for confidence.

In some embodiments the method may involve Models and Derivations forpredicting the type of cancer present in a patient based on results RNAexpression in combination with demographic or lifestyle attribute(s).

In some embodiments cfRNA levels may be assayed using sequencingtechnology. Examples of sequencing technology include but are notlimited to one or more technologies such as pyrosequencing, e.g., ‘the'454’ method (Margulies et al., (2005) Genome sequencing inmicrofabricated high-density picolitre reactors. Nature 437:376-380;Ronaghi, et al. (1996) Real-time DNA sequencing using detection ofpyrophosphate release. Anal. Biochem. 242:84-89), ‘Solexa’ orIllumina-type sequencing (Fedurco et al., (2006), BTA, a novel reagentfor DNA attachment of glass and efficient generation of solid-phaseamplified DNA colonies. Nucleic Acid Research 34, e22; Turcatti et al.(2008), A new class of cleavable fluorescent nucleotides: synthesis andoptimization as reversible terminators for DNA sequencing by synthesis.Nucleic Acid Research 36, e25), SOLiD sequencing technology (Shendure,J. et al. (2005) Accurate multiplex polony sequencing of an evolvedbacterial genome. Science 309, 1728-1732; McKernan, K. et al, (2006)Reagents, methods, and libraries for bead-based sequencing. US patentapplication 20080003571), Heliscope Technology (Harris, T. D. et al.(2008) Single-molecule DNA sequencing of a viral genome. Science 320,106-109), Ion Torrent Technology (Rothberg et al., (2011) An integratedsemiconductor device enabling non-optical genome sequencing. Nature 475,348-352), SMRT Sequencing Technology (Pacific Biosciences), or GridIONnanopore-based sequencing (Oxford Nanopore Technologies;http://www.nanoporetech.com/technology/the-gridion-system/the-gridion-system).In some embodiments any number of so-called ‘next generation’ DNAsequencing methods may be used, as described in Shendure and Ji,“Next-generation DNA sequencing”, Nature Biotechnology 26(10):1135-1145(2008) or in other art available to one of skill in the art. Othermethods for the determination of DNA sequence are also known in the art,and embodiments disclosed herein are not limited to any particularmethod of determining base identity at a particular locus to theexclusion of any other method.

In some embodiments, the cfRNA levels may be assayed via hybridizationto a microarray, nCounter or similar. For example, one class of arrayscommonly used in differential expression studies includes microarrays oroligonucleotide arrays. These arrays utilize a large number of probesthat are synthesized directly on a substrate and are used to interrogatecomplex RNA or message populations based on the principle ofcomplementary hybridization. Typically, these microarrays provide setsof 16 to 20 oligonucleotide probe pairs of relatively small length(20mers-25mers) that span a selected region of a gene or nucleotidesequence of interest. The probe pairs used in the oligonucleotide arraymay also include perfect match and mismatch probes that are designed tohybridize to the same RNA or message strand. The perfect match probecontains a known sequence that is fully complementary to the message ofinterest while the mismatch probe is similar to the perfect match probewith respect to its sequence except that it contains at least onemismatch nucleotide which differs from the perfect match probe. Duringexpression analysis, the hybridization efficiency of messages from asample nucleotide population are assessed with respect to the perfectmatch and mismatch probes in order to validate and quantitate the levelsof expression for many messages simultaneously. In some embodiments anentire gene array is printed to a microarray. In some embodiments asubset of genes comprising FPR1 and at least one of ACTB and HNRNPA1 isincluded on a microarray. In some embodiments a microarray comprises atleast FPR1, ACTB and HNRNPA1.

A device such as an nCounter, offered by Nanostring technologies, forexample, may be used to facilitate analysis. An nCounter Analysis Systemis an integrated system comprising a fully automated prep station, adigital analyzer, the CodeSet (molecular barcodes) and all of thereagents and consumables needed to perform the analysis. Analysis on thenCounter system consists of in-solution hybridization,post-hybridization processing, digital data acquisition, andnormalization in one simple workflow. In some embodiments the process isautomated. In some embodiments custom or pre-designed sets of barcodedprobes may be pre-mixed with a comprehensive set of system controls aspart of said analysis.

A number of methods of and devices for obtaining the cfRNA transcriptaccumulation level data necessary to perform the methods and for usewith the compositions and kits disclosed herein, and no single dataaccumulation method or device should be seen as limiting.

EXAMPLES Example 1

Plasma was collected from patients known to have non-small cell lungcancer (“NSCLC”) and patients without any known lung cancer (putatively“cancer free” individuals). There is some possibility that patientswithout any known lung cancer may in fact have an otherwise undetectedcancer. The presence of these patients will lead to an over-estimationof the false positive rate for this test (because “false positives” from“healthy individuals” may in fact represent the presence of cancer inthese individuals). After removing plasma that had obvious issues, suchas orange color or turbidity, 25 cancer-free and 26 NSCLC plasma samplesremained. The following stages of cancer were present from the 26 NSCLCpatients: 8 stage I, 6 stage II, 5 stage III, and 7 stage unknown. Theplasma was extracted with the QIAamp circulating nucleic acid kit(Qiagen #55114). The Quantifast Probe RT-PCR Plus Kit (Qiagen #204484)was used along with the previously described primers and probes forFPR1, ACTB, and HNRNPA1 to conduct quantitative Taqman PCR. UniversalHuman Reference RNA (Agilent #740000) was used as a standard, andregression was used to estimate quantities of each gene in the sample(FIG. 2A). Samples with a ratio of ACTB/HNRNPA1 above 75 were eliminatedfrom the final results, and given a result of “no result”. The followingresults were obtained. Note that the x-axis is the ratio of FPR1/ACTBand the Y-axis is the ratio of FPR1/HNRNPA1.

As shown in FIG. 1A, FPR1 median accumulation levels normalized againstaccumulation levels measured in Universal Human Reference RNA differedby about 100-fold between Normal and Tumor patient populations.Similarly, the upper limit of the 25% quartile of the Normal patentpopulation was measurably below the lower limit 75% quartile of themeasurements for the Tumor patient population. The highest, rarestextreme Normal measurements occasionally were as high as, but no higherthan, the Tumor patient median values.

This result shows that measuring the circulating free RNA levels of FPR1allows one to predict the presence of cancer in a patient.

As shown in FIG. 1B, ACTB median accumulation levels did not differsignificantly between Normal and Tumor patient populations. There wasalso substantial overlap at the 25%-75% quartile range and among theextreme outliers in accumulation levels between Normal and Tumor patientpopulations.

Similarly, in FIG. 1C, HNRNPA1 median accumulation levels did not differsignificantly between Normal and Tumor patient populations. There wasalso substantial overlap at the 25%-75% quartile range and among theextreme outliers in accumulation levels between Normal and Tumor patientpopulations.

This result demonstrates the suitability of ACTB and HNRNPA1 as subset#2 constituents or as reference standards.

As shown in FIG. 2A, when a cell line control was used, Tumor and NormalSample results were significantly different from one another. Despitethe presence of some overlap, NSCLC samples consistently showed FPR1 toACTB ratios and FPR1 to HNRNPA1 ratios that were in generalsignificantly greater than the corresponding values obtained for a cellline control.

This experiment shows that comparing the circulating free RNA levels ofFPR1 to the circulating free RNA levels of HNRNPA1 or ACTB allows one topredict the presence of cancer in a patient.

Example 2

A second set of 6 NSCLC and 7 Normal patient samples were assayed usinga protocol similar to that discussed in Example 1. Two technicalmodifications were made: plasma was extracted via the QIAsymphony DSPVirus/Pathogen Midi Kit (Qiagen 937055) and a synthetic standard asdescribed above was used. Additional samples were excluded after ascreen for obvious issues such as cloudiness or discoloration. Theratios of the fitted values for each gene were determined, and are shownin FIG. 2B. The X and Y axis are the same ratios as previouslydescribed.

As shown in FIG. 2B, when a synthetic standard was used, NSCLC andNormal Sample results were significantly different from one another.NSCLC samples consistently showed ACTB to FPR1 ratios and HNRNPA1 toFPR1 ratios that were significantly greater than the correspondingvalues obtained for plasma obtained from cancer-free individuals. Asimple line can be drawn to separate all but one of the Normal syntheticstandard result ratios from all of the NSCLC results.

While it may initially appear that there is a wider gap between theNSCLC and cancer-free group, this may be due to the smaller number ofpoints. As fewer points are present, extreme values are less probable.Some reduction in variability may also be due to the smaller number ofdilutions used creation of the synthetic standard. This is enabled bythe ability to fine tune the concentration of each gene individually inthe standard.

Example 3

Plasma was collected from a patient suspected of having lung cancer.FPR1, ACTB and HNRNPA1 transcript accumulation levels in the cfRNApopulation of said patient were determined from the patient's plasma asdescribed above. Patient FPR1 accumulation levels were compared tolevels known to correspond with healthy individuals and with individualsthat have cancer, for example, the accumulation levels indicated in FIG.1A. Other reference measures of FPR1 accumulation in cfRNA of healthyand cancer-positive individuals could also have been used. An arbitraryvalue of 100 was assigned to the full concentration of the standard foreach gene, with the two additional dilutions used to create the standardcurve being 10 and 1 arbitrary units. Sample 171 was collected from apatient known to have NSCLC. The values of 18.14, 26.64 and 5.38 wereobtained for FPR1, ACTB and HNRNPA1 respectively. The score wascalculated as 18.14/(26.64+5.38)=0.567 was obtained. Because this valueis greater than 0.5, a positive result for NSCLC was obtained.

Plasma was collected from patient 164 with no evidence of cancer.Transcript accumulation levels of FPR1, ACTB and HNRNPA1 were obtainedas above. The values of 3.53, 12.2 and 2.87 were obtained for FPR1, ACTBand HNRNPA1 respectively. The score is calculated as3.53/(12.2+2.87)=0.234 was obtained. Because this value is less than0.5, a negative result for NSCLC was obtained.

This experiment shows that determining the circulating free RNA levelsof FPR1, ACTB and HNRNPA1 allows one to predict the presence of cancer,and particularly lung cancer, in a patient.

Example 4

Plasma is collected from a patient suspected of having lung cancer. FPR1transcript accumulation levels in the cfRNA population of said patientare determined from the patient's plasma as described above. PatientFPR1 accumulation levels are compared to levels known to correspond withhealthy individuals and with individuals that have cancer, for example,the accumulation levels indicated in FIG. 1A. Other reference measuresof FPR1 accumulation in cfRNA of healthy and cancer-positive individualsmay be used. Levels are found to be 60,000 FPR1 molecules per mL, whichcorresponds to the median accumulation level observed for Tumor patientsbut is at or above the extreme highest measured value for Normalpatients.

This FPR1 accumulation level indicates with a high degree of confidencethat a NSCLC cell population is present in the patient.

Plasma is collected from a second patient suspected of having lungcancer. FPR1 transcript accumulation levels in the cfRNA population ofsaid patient are determined and compared as above. Levels are found tobe 600 FPR1 molecules per mL, which corresponds to the medianaccumulation level observed for Normal patients but is at or below theextreme lowest measured value for Tumor patients. This FPR1 accumulationlevel indicates with a high degree of confidence that the patient isfree of a cancerous or precancerous cell population detectable throughthis method.

This experiment shows that determining the circulating free RNA levelsof FPR1 allows one to predict the presence of cancer in a patient.

What is claimed is:
 1. A method of assaying for the presence of cancerand of precancerous cells in a person, comprising: providing abiological sample from a patient suspected of having cancer; measuringthe circulating free level of nucleic acids from a formylpeptidereceptor gene in the biological sample; and comparing the measured levelof said formylpeptide receptor gene with known levels of said gene inhealthy persons, wherein an increased level indicates the presence ofcancer in the patient.
 2. The method of claim 1, wherein saidformylpeptide receptor gene is FPR1.
 3. The method of claim 1, whereinthe comparing comprises electronically comparing in a computer valuesreflective of said circulating free levels of said gene.
 4. The methodof claim 1, wherein the sample comprises blood components.
 5. The methodof claim 4, wherein the blood components comprise plasma.
 6. The methodof claim 1, wherein said measuring comprises normalizing said transcriptaccumulation levels to a standard.
 7. The method of claim 6, wherein thestandard is a synthetic standard.
 8. The method of claim 6, wherein thestandard comprises RNA extracted from a standard cell line.
 9. Themethod of claim 1, wherein said measuring comprises comparing said genelevels to the circulating free levels of nucleic acids of a secondpopulation that are known to be present at stable levels independent ofcancer status.
 10. The method of claim 1 wherein the cancer is lungcancer
 11. The method of claim 10 wherein the cancer is non-small celllung cancer.
 12. The method of claim 9 wherein the circulating freenucleic acids comprise circulating free ribonucleic acids.
 13. Themethod of claim 12 wherein the circulating free nucleic acids comprisecirculating free messenger ribonucleic acids (mRNA).
 14. A kit for thedetermination of the presence of cancer in a patient, comprising: acontainer comprising amplification primers for amplifying circulatingfree RNA corresponding to the formylpeptide receptor gene (FPR1) genefrom a biological sample.
 15. The kit of claim 14, wherein theamplification primers have the nucleic acid sequences of:Forward Primer: 5′ (SEQ ID NO: 1) TGACGGTGAGAGGCATCA 3′Reverse Primer: 5′ (SEQ ID NO: 3) GGTGGCAATAAGCCCATAACTG 3′


16. A method for assaying for the presence of cancer and of precancerouscells in a person, comprising the steps of: providing a samplecomprising blood or blood components from a patient suspected of havinglung cancer; measuring the circulating free level of nucleic acids froma formylpeptide receptor gene in the sample; and comparing the measuredlevel of said formylpeptide receptor gene with at least one referencecirculating free nucleic acid of a second gene, wherein the ratio of thelevel of circulating free formylpeptide receptor gene to the level ofthe reference gene indicates the presence of lung cancer in the patient.17. The method of claim 16, wherein the sample comprises plasma.
 18. Themethod of claim 16, wherein the formylpeptide receptor gene is FPR1. 19.The method of claim 16, wherein said reference circulating free nucleicacid of said second gene comprises circulating free RNA levels fromActin B (ACTB).
 20. The method of claim 16, wherein said referencecirculating free nucleic acid of said second gene comprises circulatingfree RNA levels of HNRNPA1.
 21. The method of claim 16, wherein saidreference circulating free nucleic acid comprises circulating free RNAlevels of both ACTB and HNRNPA1.
 22. The method of claim 16, whereinsaid nucleic acid accumulation levels are normalized to a syntheticreference standard.
 23. The method of claim 22, wherein said syntheticreference standard comprises template nucleic acids at concentrationswithin an order of magnitude of expected accumulation levels in apatient sample.
 24. The method of claim 23, wherein said syntheticnucleic acids comprises template nucleic acids corresponding to at leasttwo transcripts to be assayed in a patient sample, and wherein each saidreference nucleic acid population is present at a concentration withinan order of magnitude of an expected accumulation level of acorresponding transcript in a patient sample.
 25. A method for assayingfor the presence of a condition in a person, comprising the steps of:providing a sample comprising blood or blood components from a patientsuspected of having lung cancer; measuring a circulating free level ofnucleic acids from a HNRNPA1 in the sample; and comparing the measuredlevel of HNRNPA1 with a circulating free level of nucleic acids from asecond transcript, wherein the level of the second circulating freetranscript indicates said condition.
 26. The method of claim 25, whereinsaid condition is the presence of cancer or of precancerous cells insaid patient.
 27. The method of claim 26, wherein said second transcriptis FPR1.
 28. A method for creating a standard for expression analysiscomprising the steps of: selecting a first synthetic RNA templatesequence; selecting a second synthetic RNA template sequence; obtainingan estimate of an expected concentration of transcripts comprising saidfirst synthetic RNA template sequence and transcripts comprising saidsecond synthetic RNA template sequence in a biological sample; andcombining said first template sequence and said second template sequencein a composition such that the concentration of each said templatesequence corresponds to the expected concentration of each said sequencein an unknown sample.
 29. A method for evaluating the quality of aplasma-derived nucleic acid sample comprising the steps of: measuringACTB transcript accumulation levels in said sample; measuring HNRNPA1levels in said sample; comparing said ACTB accumulation levels and saidHNRNPA1 accumulation levels; and discarding said sample if saidaccumulation levels differ by greater than five times the median ratiobetween the genes.